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An accurate and reliable 3D engineering geological model (expressed herein as a 3D litho-stratigraphic model) is essential for designing slopes, underground structures, and tunnels to reduce the risk of failure. Due to budget constraints, subsurface investigations with traditional methods (e.g., boreholes and geophysical prospecting) are often limited in quantity. Insufficient investigation often leads to inadequate litho-stratigraphic data that can degrade the reliability of the developed 3D litho-stratigraphic models. To this end, LiDAR, which can collect topographic data more efficiently and economically, may complement traditional geological investigations for developing litho-stratigraphic models. However, the task of integrating the subsurface geological data and LiDAR data to create 3D litho-stratigraphic models for engineering applications is challenging. This paper proposes a methodology that combines LiDAR-derived geological data (Type I data herein) and borehole data (Type II data herein) to develop realistic 3D litho-stratigraphic models. To demonstrate the methodology, we took a 1.2 km × 1.2 km area with sedimentary rocks in northern Taiwan as the study area. Under the assumption that the strata are parallel, we first fitted Type I data to a surface regression model (a polynomial mathematical model). Then, we incorporated Type II data into the regressive process to develop the desired 3D model. Comparing the former model (based on Type I data) with the latter model (based on Type I + II data) through a Root-Mean-Squared-Error (RMSE) analysis, it was found that the RMSE of the latter model decreased significantly, indicating a decrease in the error between the developed litho-stratigraphic model and the 'ground truth.' To verify this finding, we compared the newly developed 3D model with the 'known' geological cross-section of the Qidu Tunnel constructed nearby. The results indicated that the distribution of the primary sandstone strata uncovered from the previous Qidu Tunnel project and those projected by the newly developed 3D model was highly consistent. Thus, this study demonstrates that LiDAR data combined with a few borehole data has the potential to create reliable and accurate 3D geological models, providing an effective solution for obtaining 3D geological information at the scale of engineering applications with limited boreholes. Finally, the proposed modeling approach is further demonstrated through two hypothetical engineering application cases. • 3D litho-stratigraphic modeling using LiDAR and limited borehole data. • Modeling in a dip-slope terrain was verified through ground truth along a tunnel. • Combination of LiDAR and borehole data can greatly improve the model reliability. • Precise borehole data and extensive range of LiDAR data complement each other. [ABSTRACT FROM AUTHOR]

Reservoir operations can induce massive landslides due to the regional hydraulic effects, where pile reinforcement is a widely used stabilization method. The 1-g physical modeling is one of the most common methods used to study reservoir landslides and their pile reinforcement, while some limitations have been presented in the method, slowed its development down, and adverse to novel results. This paper presents a systematic review and discussion of 1-g physical modeling relevant to pile-reinforced reservoir landslides. Various aspects, from the theoretical basis (i.e., principle of similitude) to experimental details (i.e., model construction, test technique, and data acquisition and interpretation), are investigated. The principle of similitude and application in the physical modeling of pile-reinforced reservoir landslides are discussed. Factors causing distortions in a 1-g physical landslide model are discussed, and measures for distortion control are proposed. The significance and limitations of the physical model construction and obtained data are analyzed, and some improvements are proposed. Based on previous work and our experience, the lessons learned in the technical aspects of 1-g physical modeling are presented along with recommendations for the physical modeling of landslides, especially those reinforced with piles. • A strategy of distortion compensation in 1-g physical modeling is provided as a supplement to the principle of similitude. • The lessons in technical aspects of 1-g physical modeling of reservoir landslides and pile reinforcement are discussed. • The displacement and pressure data limitations are analyzed and its improvements are proposed. [ABSTRACT FROM AUTHOR]

Soil-rock mixtures (SRMs) are heterogeneous geological bodies with complex spatial structures and peculiar mechanical properties. This paper proposes a high-precision computational modeling method to realistically simulate the shape of rock blocks in the SRMs as well as the mesostructure of SRMs. The precise control theory of the rock blocks is first described. Then, acceleration measures such as bounding volume hierarchies and position culling are introduced to increase the computational efficiency while retaining the model accuracy. Practical examples and comparisons with the existing methods are provided to demonstrate the advantageous features of this method. In the end, the modeling method is successfully integrated into the DEM platform to create engineering models involved in SRMs, which lays the foundation for further DEM analysis to understand the effects of the mesostructure on the mechanical properties of SRMs. • Computational modeling of soil-rock mixtures based on realistic shape of rock blocks. • High-precision control of the orientation, size and position of rock blocks in the sample domain. • Suitable for both convex and concave particles with massive triangular faces. • Performance optimization based on designed data structures and algorithms. • Convenient integration with engineering cases and laboratory experiments. [ABSTRACT FROM AUTHOR]